Gremlin console and spark UI not responding when performing OLAP query with JanusGraph with Apache spark - apache-spark

Question

I have a graph on Janusgraph(v0.5.3) which contains around 2 million vertices and 20 million edges. I'm making a OLAP query which is modified version of lowest_common_ancestor recipe (query added below).
The query is taking too long(more than 1 hour) and I'm seeing Managed memory leak detected; warnings and then the spark web UI doesnt respond
anymore(cant debug anymore).
Also I'm seeing Lost executor driver on localhost: Executor heartbeat timed out warnings . But the query is not exiting even after 1 hour. I see these warnings after 30 min the job is started. I
was hoping spark and hadoop would make queries faster, but this seems
very slow. I'm not able to profile the query or look into spark web UI for the progress.
Note: I have installed hadoop(3.2.2) and using Apache Spark(2.4.0 ). I'm assuming spark came with janusgraph distribution which I don't remember installing. But the JanusGraph docs says v0.5.3 is compatible with spark 2.2.x ),not sure if spark compatibility is the issue?
Below is how I'm running the query using bin/gremlin.sh console.
graph = GraphFactory.open('conf/hadoop-graph/read-cql.properties')
g = graph.traversal().withComputer(SparkGraphComputer)
// OLAP query
input = [2437272, 4956336]
g.V().has(id, within(input)).
aggregate('input').hasId(input.head()).
repeat(__.in('has_word')).emit().as('x').
select('input').unfold().has(id, within(input.tail())).
repeat(__.in('has_word')).emit(where(eq('x'))).
group().
by(select('x')).
by(path().count(local).fold()).
unfold().filter(select(values).count(local).is(input.tail().size())).
order().
by(select(values).unfold().sum()).
select(keys).limit(5).elementMap()
Im assuming hadoop is configured fine
user#xyz-WS:~/Downloads/janusgraph-full-0.5.3$ bin/gremlin.sh
\,,,/
(o o)
-----oOOo-(3)-oOOo-----
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/home/rrmerugu/Downloads/janusgraph-full-0.5.3/lib/slf4j-log4j12-1.7.12.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/home/rrmerugu/Downloads/janusgraph-full-0.5.3/lib/logback-classic-1.1.3.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory]
plugin activated: janusgraph.imports
plugin activated: tinkerpop.server
plugin activated: tinkerpop.utilities
00:56:59 WARN org.apache.hadoop.util.NativeCodeLoader - Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
plugin activated: tinkerpop.hadoop
plugin activated: tinkerpop.spark
plugin activated: tinkerpop.tinkergraph
gremlin>
gremlin> hdfs
==>storage[DFS[DFSClient[clientName=DFSClient_NONMAPREDUCE_1845984070_1, ugi=rrmerugu (auth:SIMPLE)]]]
conf/hadoop-graph/read-cql.properties as described below
#
# Hadoop Graph Configuration
#
gremlin.graph=org.apache.tinkerpop.gremlin.hadoop.structure.HadoopGraph
gremlin.hadoop.graphReader=org.janusgraph.hadoop.formats.cql.CqlInputFormat
gremlin.hadoop.graphWriter=org.apache.hadoop.mapreduce.lib.output.NullOutputFormat
gremlin.hadoop.jarsInDistributedCache=true
gremlin.hadoop.inputLocation=none
gremlin.hadoop.outputLocation=output
gremlin.spark.persistContext=true
gremlin.spark.persistStorageLevel=DISK_ONLY #MEMORY_AND_DISK
#
# JanusGraph Cassandra InputFormat configuration
#
# These properties defines the connection properties which were used while write data to JanusGraph.
janusgraphmr.ioformat.conf.storage.backend=cql
# This specifies the hostname & port for Cassandra data store.
janusgraphmr.ioformat.conf.storage.hostname=127.0.0.1
janusgraphmr.ioformat.conf.storage.port=9042
# This specifies the keyspace where data is stored.
janusgraphmr.ioformat.conf.storage.cql.keyspace=janusgraph
# This defines the indexing backend configuration used while writing data to JanusGraph.
janusgraphmr.ioformat.conf.index.search.backend=elasticsearch
janusgraphmr.ioformat.conf.index.search.hostname=127.0.0.1
# Use the appropriate properties for the backend when using a different storage backend (HBase) or indexing backend (Solr).
#
# Apache Cassandra InputFormat configuration
#
cassandra.input.partitioner.class=org.apache.cassandra.dht.Murmur3Partitioner
cassandra.input.widerows=true
#
# SparkGraphComputer Configuration
#
spark.master=local[8]
spark.executor.memory=12g
spark.driver.memory=12g
spark.serializer=org.apache.spark.serializer.KryoSerializer
spark.kryo.registrator=org.janusgraph.hadoop.serialize.JanusGraphKryoRegistrator
spark.executor.memoryOverhead=1g
spark.driver.memoryOverhead=1g
spark.network.timeout=600s
spark.executor.heartbeatInterval=119s
spark.io.compression.codec=snappy
gremlin console output
rrmerugu#Code-WS:~/Downloads/janusgraph-full-0.5.3$ bin/gremlin.sh
\,,,/
(o o)
-----oOOo-(3)-oOOo-----
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/home/rrmerugu/Downloads/janusgraph-full-0.5.3/lib/slf4j-log4j12-1.7.12.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/home/rrmerugu/Downloads/janusgraph-full-0.5.3/lib/logback-classic-1.1.3.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory]
plugin activated: janusgraph.imports
plugin activated: tinkerpop.server
plugin activated: tinkerpop.utilities
07:57:25 WARN org.apache.hadoop.util.NativeCodeLoader - Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
plugin activated: tinkerpop.hadoop
plugin activated: tinkerpop.spark
plugin activated: tinkerpop.tinkergraph
gremlin> graph = GraphFactory.open('conf/hadoop-graph/read-cql.properties')
==>hadoopgraph[cqlinputformat->nulloutputformat]
gremlin> g = graph.traversal().withComputer(SparkGraphComputer)
==>graphtraversalsource[hadoopgraph[cqlinputformat->nulloutputformat], sparkgraphcomputer]
gremlin> input = [2437272, 4956336]
==>2437272
==>4956336
gremlin> g.V().has(id, within(input)).
......1> aggregate('input').hasId(input.head()).
......2> repeat(__.in('has_word')).emit().as('x').
......3> select('input').unfold().has(id, within(input.tail())).
......4> repeat(__.in('has_word')).emit(where(eq('x'))).
......5> group().
......6> by(select('x')).
......7> by(path().count(local).fold()).
......8> unfold().filter(select(values).count(local).is(input.tail().size())).
......9> order().
.....10> by(select(values).unfold().sum()).
.....11> select(keys).limit(5).elementMap()
07:58:05 WARN org.apache.tinkerpop.gremlin.spark.process.computer.SparkGraphComputer - class org.apache.hadoop.mapreduce.lib.output.NullOutputFormat does not implement PersistResultGraphAware and thus, persistence options are unknown -- assuming all options are possible
07:58:06 WARN org.apache.spark.util.Utils - Your hostname, Code-WS resolves to a loopback address: 127.0.1.1; using 192.168.0.10 instead (on interface enp7s0)
07:58:06 WARN org.apache.spark.util.Utils - Set SPARK_LOCAL_IP if you need to bind to another address
08:01:59 WARN org.apache.spark.executor.Executor - Managed memory leak detected; size = 40472352 bytes, TID = 1633
08:02:03 WARN org.apache.spark.executor.Executor - Managed memory leak detected; size = 41050016 bytes, TID = 1683
08:11:26 WARN org.apache.spark.rpc.netty.NettyRpcEnv - Ignored failure: java.util.concurrent.TimeoutException: Cannot receive any reply from 192.168.0.10:43701 in 119 seconds
08:11:29 WARN org.apache.spark.executor.Executor - Issue communicating with driver in heartbeater
org.apache.spark.rpc.RpcTimeoutException: Futures timed out after [119 seconds]. This timeout is controlled by spark.executor.heartbeatInterval
at org.apache.spark.rpc.RpcTimeout.org$apache$spark$rpc$RpcTimeout$$createRpcTimeoutException(RpcTimeout.scala:47)
at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:62)
at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:58)
at scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:36)
at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:76)
at org.apache.spark.rpc.RpcEndpointRef.askSync(RpcEndpointRef.scala:92)
at org.apache.spark.executor.Executor.org$apache$spark$executor$Executor$$reportHeartBeat(Executor.scala:835)
at org.apache.spark.executor.Executor$$anon$2$$anonfun$run$1.apply$mcV$sp(Executor.scala:864)
at org.apache.spark.executor.Executor$$anon$2$$anonfun$run$1.apply(Executor.scala:864)
at org.apache.spark.executor.Executor$$anon$2$$anonfun$run$1.apply(Executor.scala:864)
at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1945)
at org.apache.spark.executor.Executor$$anon$2.run(Executor.scala:864)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
at java.util.concurrent.FutureTask.runAndReset(FutureTask.java:308)
at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$301(ScheduledThreadPoolExecutor.java:180)
at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:294)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.util.concurrent.TimeoutException: Futures timed out after [119 seconds]
at scala.concurrent.impl.Promise$DefaultPromise.ready(Promise.scala:219)
at scala.concurrent.impl.Promise$DefaultPromise.result(Promise.scala:223)
at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:220)
at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:75)
... 14 more
08:21:13 WARN org.apache.spark.rpc.netty.NettyRpcEnv - Ignored failure: java.util.concurrent.TimeoutException: Cannot receive any reply from 192.168.0.10:43701 in 119 seconds
08:21:37 WARN org.apache.spark.executor.Executor - Issue communicating with driver in heartbeater
org.apache.spark.rpc.RpcTimeoutException: Futures timed out after [119 seconds]. This timeout is controlled by spark.executor.heartbeatInterval
at org.apache.spark.rpc.RpcTimeout.org$apache$spark$rpc$RpcTimeout$$createRpcTimeoutException(RpcTimeout.scala:47)
at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:62)
at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:58)
at scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:36)
at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:76)
at org.apache.spark.rpc.RpcEndpointRef.askSync(RpcEndpointRef.scala:92)
at org.apache.spark.executor.Executor.org$apache$spark$executor$Executor$$reportHeartBeat(Executor.scala:835)
at org.apache.spark.executor.Executor$$anon$2$$anonfun$run$1.apply$mcV$sp(Executor.scala:864)
at org.apache.spark.executor.Executor$$anon$2$$anonfun$run$1.apply(Executor.scala:864)
at org.apache.spark.executor.Executor$$anon$2$$anonfun$run$1.apply(Executor.scala:864)
at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1945)
at org.apache.spark.executor.Executor$$anon$2.run(Executor.scala:864)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
at java.util.concurrent.FutureTask.runAndReset(FutureTask.java:308)
at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$301(ScheduledThreadPoolExecutor.java:180)
at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:294)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.util.concurrent.TimeoutException: Futures timed out after [119 seconds]
at scala.concurrent.impl.Promise$DefaultPromise.ready(Promise.scala:219)
at scala.concurrent.impl.Promise$DefaultPromise.result(Promise.scala:223)
at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:220)
at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:75)
... 14 more
08:32:07 WARN org.apache.spark.executor.Executor - Issue communicating with driver in heartbeater
08:35:18 WARN org.apache.spark.HeartbeatReceiver - Removing executor driver with no recent heartbeats: 614252 ms exceeds timeout 600000 ms
Exception in thread "dispatcher-event-loop-7" java.lang.OutOfMemoryError: Java heap space
08:44:53 ERROR org.apache.spark.util.Utils - Uncaught exception in thread driver-heartbeater
08:57:17 WARN org.spark_project.jetty.io.ManagedSelector -
java.lang.OutOfMemoryError: Java heap space
08:58:56 ERROR org.apache.spark.util.Utils - uncaught error in thread Spark Context Cleaner, stopping SparkContext
java.lang.OutOfMemoryError: Java heap space
08:58:56 ERROR org.apache.spark.util.Utils - throw uncaught fatal error in thread Spark Context Cleaner
java.lang.OutOfMemoryError: Java heap space
Exception in thread "Spark Context Cleaner" java.lang.OutOfMemoryError: Java heap space
08:58:56 ERROR org.apache.spark.executor.Executor - Exception in task 91.0 in stage 16.0 (TID 1890)
java.lang.OutOfMemoryError: Java heap space
08:58:56 ERROR org.apache.spark.util.SparkUncaughtExceptionHandler - Uncaught exception in thread Thread[Executor task launch worker for task 1890,5,main]
java.lang.OutOfMemoryError: Java heap space
08:58:56 WARN org.apache.spark.scheduler.TaskSetManager - Lost task 91.0 in stage 16.0 (TID 1890, localhost, executor driver): java.lang.OutOfMemoryError: Java heap space
08:58:56 ERROR org.apache.spark.scheduler.TaskSetManager - Task 91 in stage 16.0 failed 1 times; aborting job
org.apache.spark.SparkException: Job aborted due to stage failure: Task 91 in stage 16.0 failed 1 times, most recent failure: Lost task 91.0 in stage 16.0 (TID 1890, localhost, executor driver): java.lang.OutOfMemoryError: Java heap space
Driver stacktrace:
Type ':help' or ':h' for help.
system specs: I'm performing this on Ubuntu 6 core i7 processor with 32GB RAM and 1TB SSD.
What I want to find answers for:
Am I missing something, any hints on why this query is taking too long with errors? any suggestions appreciated.
Is there a better way to profile this query and why it's taking too long; console and spark web UI doesn't response once memory leak errors happen, and I have no way to debug this.
UPDATE
updated the log with OOM errors that the program exited with now